Introduction: Although significant progress has been made in high-throughput screening of
absorption, distribution, metabolism and excretion, and toxicity (ADME-Tox) properties in …

As expenditure on drug development increases exponentially, the overall drug discovery
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …

In recent times, machine learning has become increasingly prominent in predictive
toxicology as it has shifted from in vivo studies toward in silico studies. Currently, in vitro …

Drug-induced liver injury (DILI) is the most frequently reported single cause of safety-related
withdrawal of marketed drugs. It is essential to identify drugs with DILI potential at the early …

The ever-increasing number of chemicals has raised public concerns due to their adverse
effects on human health and the environment. To protect public health and the environment …

As one of the leading causes of drug failure in clinical trials, drug-induced liver injury (DILI)
seriously impeded the development of new drugs. Assessing the DILI risk of drug candidates …

Drug-induced liver injury (DILI) is one the most unpredictable adverse reactions to
xenobiotics in humans and the leading cause of postmarketing withdrawals of approved …

New approach methods (NAMs) have been developed to predict a wide range of toxicities
through innovative technologies. Liver injury is one of the most extensively studied …

As a critical issue in drug development and postmarketing safety surveillance, drug-induced
liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market …

Drug-induced liver injury (DILI) is a key safety issue in the drug discovery pipeline and a
regulatory concern. Thus, many in silico tools have been proposed to improve the …